The evolution of white matter microstructural changes after mild traumatic brain injury: A longitudinal DTI and NODDI study

Association of aberrant gray matter neurite density with neurovegetative symptom in atypical depression

BACKGROUND

The heterogeneity of symptoms in major depressive disorder is impeding progress toward patient-specific treatment strategies and course trajectories. Origins of such differential clinical manifestations likely have dissociable pathophysiologies, but neural substrates associated with specific atypical depressive symptoms remain elusive.

METHODS

The muti-shell diffusion MRI images were acquired from 50 patients with atypical depression (AD), 97 patients with non-atypical depression (non-AD), and 50 healthy controls (HCs). We used gray matter-specific multi-compartment diffusion models (cortical-neurite orientation dispersion and density imaging and free-water elimination model) to assess abnormalities of gray matter microstructure associated with AD. Superficial U-fibers analysis was performed to clarify short-range cortico-cortical connections.

RESULTS

Abnormalities in intracellular volume fraction (ICVF) and free-water fraction anisotropy were found in the superior frontal gyrus, middle frontal gyrus, inferior parietal gyrus, and superior parietal gyrus across three groups. Post-hoc pairwise comparative analysis yielded similar results. While adjusting for the effects of age, gender, education, and the ICVF mentioned above, AD patients showed significantly higher scores in reversed neurovegetative symptoms and leaden paralysis compared with non-AD patients. Moreover, diagnosis-related alterations in ICVF of right caudal middle frontal gyrus and education-related changes in ICVF of right superior frontal gyrus were significantly associated with hypersomnia. We also found that underlying superficial U-fibers reflected deficits in cortical-derived neurite density.

CONCLUSIONS

Cortical-derived neurite density abnormalities were significantly associated with atypical depressive symptoms, capturing interindividual etiological heterogeneity in patients with major depressive disorder. Cortical-derived neurite density within the medial prefrontal gyrus may be a robust biomarker for atypical depressive symptoms of AD.

Causal relationship between bulimia nervosa and microstructural white matter: evidence from Mendelian randomization

PURPOSE

Observational studies suggest white matter (WM) microstructural anomalies are linked to bulimia nervosa (BN), but a direct causal relationship remains unestablished. This study aimed to investigate the causal impact of BN on WM microstructure.

METHODS

We analyzed genome-wide association study (GWAS) summary data from 2442 individuals to identify genetically predicted BN. Diffusion MRI were obtained from the UK Biobank. After assessing instrumental variable validity, we conducted Mendelian randomization (MR) using inverse variance weighting (IVW) as the primary method, followed by pleiotropy and heterogeneity tests.

RESULTS

The MR analysis from BN to brain imaging-derived phenotypes showed that BN had significant causal effects on a union set of nine tracts (including a total of 18 image-derived phenotypes) (IVW, P < 0.05): brainstem tracts (pontine crossing tract, bilateral medial lemniscus, left superior cerebellar peduncle, and middle cerebellar peduncle), sensory-related tracts (right retrolenticular part of the internal capsule and left inferior longitudinal fasciculus), and emotion-related tracts (left anterior corona radiata and right cingulum hippocampus).

CONCLUSION

This study revealed that BN has a causal effect on WM microstructure, which extends the reports of association to causation for WM and BN. These causal effects may explain the deficits in feeding, taste, vision, and emotion regulation that are often observed in patients with BN. Level of evidence III well-designed cohort analytic study.

Predominant white matter microstructural changes over gray matter in tinnitus brain

INTRODUCTION

To explore microstructure changes across brain white matter and gray matter in tinnitus patients and its effect on neuropsychological performance.

METHODS

The cross-sectional study used Multi-shell Diffusion Weighted Imaging data and neuropsychological assessment from 48 tinnitus patients and 48 healthy controls. Microstructural features across over white matter and gray matter based on Diffusion Tensor Imaging (DTI) and Neurite Orientation Dispersion and Density Imaging (NODDI) model using Tract-Based Spatial Statistics (TBSS) and Gray Matter-Based Spatial Statistics (GBSS), as well as topological properties were derived from an advanced tractography model in subjects. Brain-neuropsychological performance correlations were analyzed.

RESULTS

Tinnitus patients showed decreased axial diffusivity in forceps minor and right corticospinal tract, increased orientation dispersion in forceps minor, decreased connection strength between the right caudate and pericalcarine, right caudate and superior temporal lobe, and left putamen and cuneus. Global network efficiency and local network efficiency were significantly less in tinnitus patients while feeder connection strength was significantly less in tinnitus patients. The orientation dispersion value mediated the relationship between tinnitus status and Trail Making Test-Part B scores. However, no obvious microstructural changes in gray matter were observed.

CONCLUSION

Leveraging multi-shell DWI data, the current study indicated that fiber disruption and internal connectivity organizational changes in brain white matter, rather than gray matter, were more susceptible in tinnitus patients. These microstructural changes in white matter could be associated with changes in cognitive function in tinnitus patients.

Cognitive implications of white matter microstructural changes in individuals with low heart rate variability: a NODDI study

Objective

This study aimed to investigated the microstructural integrity of WM and the relationship with the cognitive domains and cognition-related plasma biomarkers in low heart rate variability (HRV).

Methods

Our study recruited 44 high HRV and 44 low HRV (Grouping by median of HF). Diffusion Magnetic resonance imaging (MRI) was utilized for the calculation of neurite orientation dispersion and density imaging (NODDI) parameters, and tract-based spatial statistics (TBSS) were employed to explore differential clusters. The fibers covered by these clusters were defined as regions of interest (ROI) for the extraction of NODDI parameter values and the analysis of their correlation with cognitive domains and cognition-related plasma biomarkers.

Results

The TBSS analysis unveiled specific cerebral regions exhibiting disparities within the low HRV group high HRV group. These differences were evident in fractional isotropy (FISO; p < 0.05). The extracted values from these ROIs (p < 0.05) were mainly manifested in the anterior regions of the brain and corpus callosum. Further analysis showed that the abnormal white matter (WM) showed significant correlations with CDR, RCFT-I, RCFT-D, attention, memory, language, and cognition-related plasma biomarkers to varying degrees.

Conclusion

Patients with low HRV exhibit distinctive patterns of microstructural changes in the WM as revealed by the FISO which indicate a decline in white matter integrity, and the relationship between low HRV-related and worse cognitive performance may be attributed to damage of the frontal-corpus callosum pathways.

Aberrant interhemispheric resting state functional connectivity and corpus callosum microstructure in acute carbon monoxide poisoning

Acute carbon monoxide poisoning (ACOP) is a significant contributor to acute poisoning incidents worldwide, with numerous patients suffering from cognitive impairment. Growing evidence indicates that patients with ACOP exhibit both disrupted functional connectivity and corpus callosum (CC) degeneration. Nevertheless, how interhemispheric connectivity is altered in ACOP and how such alterations relate to cognitive deficits remain largely unexplored. In this study, multimodal magnetic resonance imaging was performed on 30 patients with ACOP and 28 healthy controls (HC), and their cognitive functions were evaluated. Group differences in the voxel-mirrored homotopic connectivity (VMHC) index and CC white matter microstructure were analyzed. Furthermore, mediation analysis was conducted to elucidate the interrelationships among CC integrity, interhemispheric connectivity, and cognitive impairment. Compared to HC, patients with ACOP exhibited reduced VMHC values in the middle frontal gyrus, inferior parietal lobule, precentral gyrus, and temporal regions, along with decreased fractional anisotropy values in the subregions of the CC, including the genu, body, and splenium. Partial correlation analyses showed that VMHC in the inferior parietal lobule positively correlated with Glasgow Coma Scale scores. In addition, VMHC in both the inferior parietal lobule and the middle temporal gyrus positively correlated with Montreal Cognitive Assessment-Basic scores. Mediation analysis indicated that changes in interhemispheric connectivity played a crucial role in mediating the effect of CC integrity on cognitive impairment. Together, these findings may offer novel insights into the neurobiological mechanisms underlying ACOP.

Application of neurite orientation dispersion and density imaging in characterizing brain microstructural changes in classical trigeminal neuralgia and a comparison between the left and right sides

ABSTRACT

Diffusion tensor imaging can detect brain white matter changes in classical trigeminal neuralgia (TN). However, it lacks specificity for individual tissue microstructural features, such as neurite density, orientation dispersions, and extracellular edema. Neurite orientation dispersion and density imaging (NODDI), a novel diffusion magnetic resonance imaging (MRI) technique, can provide these distinct indices. We characterized brain microstructural alterations in patients with unilateral TN using NODDI and compared the difference between left- and right-side TN (LTN and RTN, respectively). Diffusion-weighted imaging was performed on 39 patients with LTN, 37 patients with RTN, and 37 healthy controls. Neurite orientation dispersion and density imaging-related indices, including the intracellular volume fraction (Vic), orientation dispersion index (ODI), and isotropic volume fraction (Fiso), were estimated and compared using tract-based spatial statistics and voxel-based region-of-interest analysis. The LTN and RTN groups exhibited microstructural abnormalities in white and gray matter as measured by decreased fractional anisotropy and Vic and elevated Fiso, respectively. These alterations were associated with clinical features and were mainly located in the frontal lobe, corona radiata, internal capsule, and thalamus. The angular variation of neurites, characterized by ODI, exhibited no significant changes between TN and control groups. Patients with classical TN of either side exhibited reduced Vic and increased Fiso, which indicated decreased density of axons and dendrites and neuroinflammatory edema in bilateral hemispheres. Neurite orientation dispersion and density imaging is a useful technique for in vivo diffusion MRI of white and gray matter in the brain, which provides additional metrics and information closely related to the tissue microstructure that merits further study of TN pathogenesis.

Investigating omega-3 fatty acids' neuroprotective effects in repetitive subconcussive neural injury: Study protocol for a randomized placebo-controlled trial

Soccer (football) is the most popular sport globally, with 265 million players across all ages and sexes. Repetitive subconcussive head impacts due to heading of the soccer ball can pose threats to healthy brain development and aging. Omega-3 fatty acids, especially docosahexaenoic acid (DHA) and eicosapentaenoic acid (EPA), may have neuroprotective effects, but it remains unclear what aspects of neural health benefit from DHA+EPA when faced with subconcussive head impacts. In a randomized placebo-controlled trial, 208 soccer players will complete baseline measures including demographics, blood sampling, dietary recalls, and psychological assessment. Participants will be randomly assigned to ingest DHA+EPA [3.4g/d: DHA 2.4g+EPA 1.0g] or placebo daily for 8 weeks followed by a subconcussion intervention phase. During the subconcussion intervention, participants will perform a session of 20 controlled soccer headings, with a second session 24 hours later. Blood samples, neuroimaging data, autonomic reactivity, and clinical measures (symptoms, oculomotor, cognition) will be collected pre-heading and 24-hour post-1st session, 24-hour post-2nd session, and 7-day post-2nd session. The primary hypothesis is that DHA+EPA pretreatment will promote neuronal and astrocyte resiliency to subconcussive head impacts, as assessed by blood biomarkers of brain injury, axonal microstructure measured by diffusion tensor imaging, and whole-brain resting-state connectivity. It is proposed that pretreatment will preserve autonomic function, as assessed by the cold pressor test (CPT), as well as oculomotor and cognitive function, even after head impacts. Data from this trial will help clarify the combined effect of DHA+EPA on brain molecular, cellular, and physiological health in response to subconcussive head impacts. If the hypotheses are confirmed, the findings will support a highly practical intervention for mitigating the neurodegenerative cascade triggered by head impacts. Trial registration: ClinicalTrials.gov NCT06736925.

Diffusion Tensor Imaging as Neurologic Predictor in Patients Affected by Traumatic Brain Injury: Scoping Review

Background: Diffusion tensor imaging (DTI), a variant of Diffusion Weighted Imaging (DWI), enables a neuroanatomical microscopic-like examination of the brain, which can detect brain damage using physical parameters. DTI's application to traumatic brain injury (TBI) has the potential to reveal radiological features that can assist in predicting the clinical outcomes of these patients. What is the ongoing role of DTI in detecting brain alterations and predicting neurological outcomes in patients with moderate to severe traumatic brain injury and/or diffuse axonal injury? Methods: A scoping review of the PubMed, Scopus, EMBASE, and Cochrane databases was conducted according to the Preferred Reporting Items for Systematic Reviews and Meta-Analysis (PRISMA) guidelines. The aim was to identify all potentially relevant studies concerning the role of DTI in TBI. From an initial pool of 3527 publications, 26 articles were selected based on relevance. These studies included a total of 729 patients with moderate to severe TBI and/or diffuse axonal injury. DTI parameters were analyzed to determine their relationship with neurological outcomes post-TBI, with assessments of several brain functions and regions. Results: The studies included various DTI parameters, identifying significant relationships between DTI variations and neurological outcomes following TBI. Multiple brain functions and regions were evaluated, demonstrating the capability of DTI to detect brain alterations with higher accuracy, sensitivity, and specificity than MRI alone. Conclusions: DTI is a valuable tool for detecting brain alterations in TBI patients, offering enhanced accuracy, sensitivity, and specificity compared to MRI alone. Recent studies confirm its effectiveness in identifying neurological impairments and predicting outcomes in patients following brain trauma, underscoring its utility in clinical settings for managing TBI.

Long-term neurobehavioral and neuroimaging outcomes in athletes with prior concussion(s) and head impact exposure

Objective: The long-term health of former athletes with a history of multiple concussions and/or repetitive head impact (RHI) exposure has been of growing interest among the public. The true proportion of dementia cases attributable to neurotrauma and the neurobehavioral profile/sequelae of multiple concussion and RHI exposure among athletes has been difficult to determine. Methods: Across three exposure paradigms (i.e. group comparisons of athletes vs. controls, number of prior concussions, and level of RHI exposure), this review characterizes the prevalence of neurodegenerative/neurological disease, changes in cognitive and psychiatric function, and alterations on neuroimaging. We highlight sources of variability across studies and provide suggested directions for future investigations. Results: The most robust finding reported in the literature suggests a higher level of symptom endorsement (general, psychiatric, and cognitive) among those with a greater history of sport-related concussion from adolescence to older adulthood. Pathological processes (e.g. atrophy, tau deposition, and hypometabolism) may be more likely to occur within select regions (frontal and temporal cortices) and structures (thalamus and hippocampus). However, studies examining concussion(s) and RHI exposure with imaging outcomes have yet to identify consistent associations or evidence of a dose-response relationship or a threshold at which associations are observed. Discussion: Studies have not observed a simple dose-response relationship between multiple concussions and/or RHI exposure with cognitive, psychiatric, or in vivo neurobiological outcomes, particularly at lower levels of play. The relationship between prior concussion and RHI exposure with long-term outcomes in former athletes is complex and likely influenced by -several non-injury-related factors.

Microstructural Alterations of Gray and White Matter in Active Young Boxers with Sports-Related Concussions

The existing research on the microstructural alterations associated with sport-related concussions (SRCs) has primarily focused on deep white matter (DWM) fibers, while the impact of SRCs on the superficial white matter (SWM) and gray matter (GM) remains unknown. This study aimed to characterize the altered metrics obtained from neurite orientation dispersion and density imaging (NODDI) in boxers with SRCs, and thereby determine whether distinct regional patterns of microstructural alterations can offer valuable insights for accurate diagnosis and prognosis. Concussed boxers (n = 56) and healthy controls (HCs) with typically developing (n = 72) underwent comprehensive neuropsychological assessment and magnetic resonance imaging (MRI) examinations. The tract-based spatial statistics approach was used to investigate alterations in the DWM and SWM, while the gray matter-based spatial statistics approach was used to examine changes in the GM. The median time from the last SRC to MRI in the SRC group was 33.5 days (interquartile range, 45.25). In comparison with HCs, the SRC group exhibited lower fractional anisotropy (FA), neurite density index (NDI), and isotropic volume fraction (ISOVF), as well as higher mean diffusivity, axial diffusivity (AD), and radial diffusivity in both the DWM and SWM. Moreover, the SRC group exhibited lower FA, NDI, orientation dispersion index, and ISOVF in the GM, as well as higher AD. The altered microstructure of both gray and white matter was found to be associated with deficits in working memory and vocabulary memory among boxers. In addition to characterizing the DWM impairment, NODDI further elucidated the effects of SRCs on the microstructure of GM and SWM, offering a reliable imaging biomarker for SRC diagnosis and shedding light on the pathophysiological changes underlying SRCs.

Goal-Oriented Attentional Self-Regulation Training in Chronic Mild Traumatic Brain Injury is Linked to Microstructural Plasticity in Prefrontal White Matter

Impaired attention is one of the most common, debilitating, and persistent consequences of traumatic brain injury (TBI), which impacts overall cognitive and executive functions in these patients. Previous neuroimaging studies, trying to understand the neural mechanism underlying attention impairment post TBI, have highlighted the role of prefrontal white matter tracts in attentional functioning in mild TBI (mTBI). Goal-Oriented Attentional Self-Regulation (GOALS) is a cognitive rehabilitation training program that targets executive control functions in participants by applying mindfulness-based attention regulation and goal management strategies. GOALS training has been demonstrated to improve attention and executive functioning in patients with chronic TBI. However, its impact on microstructural integrity of attention-associated prefrontal white matter tracts is still unclear. Here, using diffusion magnetic resonance imaging in a pilot randomized controlled trial, we investigated the effect of GOALS training on prefrontal white matter microstructure in 19 U.S. military veterans with chronic mTBI, compared with a matched control group of 14 veterans with chronic mTBI who received standard of care brain health education. We also tested for an association between microstructural white matter changes and sustained attention ability in these patients pre- and post-GOALS training. Our results show significantly better white matter microstructural integrity in left and right anterior corona radiata (ACR) in the GOALS group compared with the control group post-training. Moreover, we found a significant correlation between sustained attention ability of GOALS training participants and white matter integrity of their right ACR pre- and post-training. Finally, our findings indicated that the improved white matter integrity of the ACR in GOALS training participants was the result of increased neurite density and decreased fiber orientation dispersion within this tract.

Neurite Orientation Dispersion and Density Imaging (NODDI) reveals white matter microstructural changes in Obstructive Sleep Apnea Hypopnea Syndrome (OSAHS) patients with cognitive impairment

PURPOSE

This study aimed to assess changes in white matter microstructure among patients undergoing obstructive sleep apnea hypopnea syndrome (OSAHS) complicated by cognitive impairment through neurite orientation dispersion and density imaging (NODDI), and evaluate the relationship to cognitive impairment as well as the diagnostic performance in early intervention.

METHODS

Totally 23 OSAHS patients, 43 OSAHS patients complicated by cognitive impairment, and 15 healthy controls were enrolled in OSA, OSACI and HC groups of this work. NODDI toolbox and FMRIB's Software Library (FSL) were used to calculate neurite density index (NDI), Fractional anisotropy (FA), volume fraction of isotropic water molecules (Viso), and orientation dispersion index (ODI). Tract-based spatial statistics (TBSS) were carried out to examine the above metrics with one-way ANOVA. This study explored the correlations of the above metrics with mini-mental state examination (MMSE), and montreal cognitive assessment (MoCA) scores. Furthermore, receiver operating characteristic (ROC) curves were plotted. Meanwhile, area under curve (AUC) values were calculated to evaluate the diagnostic performance of the above metrics.

RESULTS

NDI, ODI, Viso, and FA were significantly different among different brain white matter regions, among which, difference in NDI showed the greatest statistical significance. In comparison with HC group, OSA group had reduced NDI and ODI, whereas elevated Viso levels. Conversely, compared to the OSA group, the OSACI group displayed a slight increase in NDI and ODI values, which remained lower than HC group, viso values continued to rise. Post-hoc analysis highlighted significant differences in these metrics, except for FA, which showed no notable changes or correlations with neuropsychological tests. ROC analysis confirmed the diagnostic efficacy of NDI, ODI, and Viso with AUCs of 0.6908, 0.6626, and 0.6363, respectively, whereas FA's AUC of 0.5042, indicating insufficient diagnostic efficacy.

CONCLUSIONS

This study confirmed that NODDI effectively reveals microstructural changes in white matter of OSAHS patients with cognitive impairment, providing neuroimaging evidence for early clinical diagnosis and intervention.

Microstructural brain changes following prospective memory rehabilitation in traumatic brain injury: An observational study

Prospective memory (PM) impairment is a common consequence of moderate-severe traumatic brain injury (TBI). Compensatory strategy training and rehabilitation (COMP) is the usual treatment of PM deficits through environmental modification and the use of assistive methods such as diaries and routines. The study intends to examine the changes in white matter integrity, as measured by advanced diffusion magnetic resonance imaging (dMRI) following COMP intervention in moderate-severe TBI patients. Nine COMP intervention and twelve routine care comparison cohort moderate-severe TBI patients were recruited from level 1 trauma centres in the Brisbane metropolitan area. Both groups were imaged at least one-month post-TBI for a baseline scan. COMP group was imaged again after a 6-week COMP intervention program and the comparison group was imaged again at least 6 weeks after the baseline scan. MRI scan included structural imaging and dMRI, which the latter fitted for the Neurite Orientation Dispersion and Density Imaging (NODDI) model. Only the comparison group had decreased Neurite Density Index in the major white matter tracts and increased isotropic diffusion in the fluid space between the cortical folds. Our results indicated that COMP intervention slowed down the neural degeneration in moderate-severe TBI patients as compared to routine medical care/rehabilitation.

Subclinical brain manifestations of repeated mild traumatic brain injury are changed by chronic exposure to sleep loss, caffeine, and sleep aids

INTRODUCTION

After mild traumatic brain injury (mTBI), the brain is labile for weeks and months and vulnerable to repeated concussions. During this time, patients are exposed to everyday circumstances that, in themselves, affect brain metabolism and blood flow and neural processing. How commonplace activities interact with the injured brain is unknown. The present study in an animal model investigated the extent to which three commonly experienced exposures-daily caffeine usage, chronic sleep loss, and chronic sleep aid medication-affect the injured brain in the chronic phase.

METHODS

Subclinical trauma by repeated mTBIs was produced by our head rotational acceleration injury model, which causes brain injury consistent with the mechanism of concussion in humans. Forty-eight hours after a third mTBI, chronic administrations of caffeine, sleep restriction, or zolpidem (sedative hypnotic) began and were continued for 70 days. On Days 30 and 60 post injury, resting state functional magnetic resonance imaging (fMRI) and diffusion tensor imaging (DTI) were performed.

RESULTS

Chronic caffeine, sleep restriction, and zolpidem each changed the subclinical brain characteristics of mTBI at both 30 and 60 days post injury, detected by different MRI modalities. Each treatment caused microstructural alterations in DTI metrics in the insular cortex and retrosplenial cortex compared with mTBI, but also uniquely affected other gray and white matter regions. Zolpidem administration affected the largest number of individual structures in mTBI at both 30 and 60 days, and not necessarily toward normalization (sham treatment). Chronic sleep restriction changed local functional connectivity at 30 days in diametrical opposition to chronic caffeine ingestion, and both treatment outcomes were different from sham, mTBI-only and zolpidem comparisons. The results indicate that commonly encountered exposures modify subclinical brain activity and structure long after healing is expected to be complete.

CONCLUSIONS

Changes in activity and structure detected by fMRI are widely understood to reflect changes in the functions of the affected region which conceivably underlie mTBI neuropathology and symptomatology in the chronic phase after injury.

Additive effects of mild head trauma, blast exposure, and aging within white matter tracts: A novel Diffusion Tensor Imaging analysis approach

Existing diffusion tensor imaging (DTI) studies of neurological injury following high-level blast exposure (hlBE) in military personnel have produced widely variable results. This is potentially due to prior studies often not considering the quantity and/or recency of hlBE, as well as co-morbidity with non-blast head trauma (nbHT). Herein, we compare commonly used DTI metrics: fractional anisotropy and mean, axial, and radial diffusivity, in Veterans with and without history of hlBE and/or nbHT. We use both the traditional method of dividing participants into 2 equally weighted groups and an alternative method wherein each participant is weighted by quantity and recency of hlBE and/or nbHT. While no differences were detected using the traditional method, the alternative method revealed diffuse and extensive changes in all DTI metrics. These effects were quantified within 43 anatomically defined white matter tracts, which identified the forceps minor, middle corpus callosum, acoustic and optic radiations, fornix, uncinate, inferior fronto-occipital and inferior longitudinal fasciculi, and cingulum, as the pathways most affected by hlBE and nbHT. Moreover, additive effects of aging were present in many of the same tracts suggesting that these neuroanatomical effects may compound with age.

Serum lipidome associates with neuroimaging features in patients with traumatic brain injury

Acute traumatic brain injury (TBI) is associated with substantial abnormalities in lipid biology, including changes in the structural lipids that are present in the myelin in the brain. We investigated the relationship between traumatic microstructural changes in white matter from magnetic resonance imaging (MRI) and quantitative lipidomic changes from blood serum. The study cohort included 103 patients from the Collaborative European NeuroTrauma Effectiveness Research in TBI (CENTER-TBI) study. Diffusion tensor fitting generated fractional anisotropy (FA) and mean diffusivity (MD) maps for the MRI scans while ultra-high-performance liquid chromatography quadrupole time-of-flight mass spectrometry was applied to analyze the lipidome. Increasing severity of TBI was associated with higher MD and lower FA values, which scaled with different lipidomic signatures. There appears to be consistent patterns of lipid changes associating with the specific microstructure changes in the CNS white matter, but also regional specificity, suggesting that blood-based lipidomics may provide an insight into the underlying pathophysiology of TBI.

Axonal injury, sleep disturbances, and memory following traumatic brain injury

OBJECTIVES

Traumatic brain injury (TBI) is associated with sleep deficits, but it is not clear why some report sleep disturbances and others do not. The objective of this study was to assess the associations between axonal injury, sleep, and memory in chronic and acute TBI.

METHODS

Data were acquired from two independent datasets which included 156 older adult veterans (69.8 years) from the Alzheimer's Disease Neuroimaging Initiative (ADNI) with prior moderate-to-severe TBIs and 90 (69.2 years) controls and 374 (39.6 years) from Transforming Research and Clinical Knowledge in TBI (TRACK-TBI) with a recent mild TBI (mTBI) and 87 controls (39.6 years), all who completed an MRI, memory assessment, and sleep questionnaire.

RESULTS

Older adults with a prior TBI had a significant association between axonal injury and sleep disturbances [β = 9.52, 95% CI (4.1, 14.9), p = 0.01]. Axonal injury predicted changes in memory over 1-year in TBI [β = -8.72, 95% CI (-18, -2.7), p = 0.03]. We externally validated those findings in TRACK-TBI where axonal injury within 2 weeks after mTBI was significantly associated with higher sleep disturbances in the TBI group at 2 weeks[β = -7.2, 95% CI (-14, -0.50), p = 0.04], 6 months [β = -16, 95% CI (-24, -7.6), p ≤ 0.01], and 12 months post-injury [β = -11, 95% CI (-19, -0.85), p = 0.03]. These associations were not significant in controls.

INTERPRETATIONS

Axonal injury, specifically to the left anterior internal capsule is robustly associated with sleep disturbances in multiple TBI populations. Early assessment of axonal injury following mTBI could identify those at risk for persistent sleep disturbances following injury.

Identification and Connectomic Profiling of Concussion Using Bayesian Machine Learning

Accurate early diagnosis of concussion is useful to prevent sequelae and improve neurocognitive outcomes. Early after head impact, concussion diagnosis may be doubtful in persons whose neurological, neuroradiological, and/or neurocognitive examinations are equivocal. Such individuals can benefit from novel accurate assessments that complement clinical diagnostics. We introduce a Bayesian machine learning classifier to identify concussion through cortico-cortical connectome mapping from magnetic resonance imaging in persons with quasi-normal cognition and without neuroradiological findings. Classifier features are generated from connectivity matrices specifying the mean fractional anisotropy of white matter connections linking brain structures. Each connection's saliency to classification was quantified by training individual classifier instantiations using a single feature type. The classifier was tested on a discovery sample of 92 healthy controls (HCs; 26 females, age μ ± σ: 39.8 ± 15.5 years) and 471 adult mTBI patients (158 females, age μ ± σ: 38.4 ± 5.9 years). Results were replicated in an independent validation sample of 256 HCs (149 females, age μ ± σ: 55.3 ± 12.1 years) and 126 patients with concussion (46 females, age μ ± σ: 39.0 ± 17.7 years). Classifier accuracy exceeds 99% in both samples, suggesting robust generalizability to new samples. Notably, 13 bilateral cortico-cortical connection pairs predict diagnostic status with accuracy exceeding 99% in both discovery and validation samples. Many such connection pairs are between prefrontal cortex structures, fronto-limbic and fronto-subcortical structures, and occipito-temporal structures in the ventral ("what") visual stream. This and related connectivity form a highly salient network of brain connections that is particularly vulnerable to concussion. Because these connections are important in mediating cognitive control, memory, and attention, our findings explain the high frequency of cognitive disturbances after concussion. Our classifier was trained and validated on concussed participants with cognitive profiles very similar to those of HCs. This suggests that the classifier can complement current diagnostics by providing independent information in clinical contexts where patients have quasi-normal cognition but where concussion diagnosis stands to benefit from additional evidence.

Usefulness of Artificial Intelligence in Traumatic Brain Injury: A Bibliometric Analysis and Mini-review

BACKGROUND

Traumatic brain injury (TBI) has become a major source of disability worldwide, increasing the interest in algorithms that use artificial intelligence (AI) to optimize the interpretation of imaging studies, prognosis estimation, and critical care issues. In this study we present a bibliometric analysis and mini-review on the main uses that have been developed for TBI in AI.

METHODS

The results informing this review come from a Scopus database search as of April 15, 2023. The bibliometric analysis was carried out via the mapping bibliographic metrics method. Knowledge mapping was made in the VOSviewer software (V1.6.18), analyzing the "link strength" of networks based on co-occurrence of key words, countries co-authorship, and co-cited authors. In the mini-review section, we highlight the main findings and contributions of the studies.

RESULTS

A total of 495 scientific publications were identified from 2000 to 2023, with 9262 citations published since 2013. Among the 160 journals identified, The Journal of Neurotrauma, Frontiers in Neurology, and PLOS ONE were those with the greatest number of publications. The most frequently co-occurring key words were: "machine learning", "deep learning", "magnetic resonance imaging", and "intracranial pressure". The United States accounted for more collaborations than any other country, followed by United Kingdom and China. Four co-citation author clusters were found, and the top 20 papers were divided into reviews and original articles.

CONCLUSIONS

AI has become a relevant research field in TBI during the last 20 years, demonstrating great potential in imaging, but a more modest performance for prognostic estimation and neuromonitoring.

Anisotropy component of DTI reveals long-term neuroinflammation following repetitive mild traumatic brain injury in rats

BACKGROUND

This study aimed to investigate the long-term effects of repetitive mild traumatic brain injury (rmTBI) with varying inter-injury intervals by measuring diffusion tensor metrics, including mean diffusivity (MD), fractional anisotropy (FA), and diffusion magnitude (L) and pure anisotropy (q).

METHODS

Eighteen rats were randomly divided into three groups: short-interval rmTBI (n = 6), long-interval rmTBI (n = 6), and sham controls (n = 6). MD, FA, L, and q values were analyzed from longitudinal diffusion tensor imaging at days 50 and 90 after rmTBI. Immunohistochemical staining against neurons, astrocytes, microglia, and myelin was performed. Analysis of variance, Pearson correlation coefficient, and simple linear regression model were used.

RESULTS

At day 50 post-rmTBI, lower cortical FA and q values were shown in the short-interval group (p ≤ 0.038). In contrast, higher FA and q values were shown for the long-interval group (p ≤ 0.039) in the corpus callosum. In the ipsilesional external capsule and internal capsule, no significant changes were found in FA, while lower L and q values were shown in the short-interval group (p ≤ 0.028) at day 90. The q values in the external capsule and internal capsule were negatively correlated with the number of microglial cells and the total number of astroglial cells (p ≤ 0.035).

CONCLUSION

Tensor scalar measurements, such as L and q values, are sensitive to exacerbated chronic injury induced by rmTBI with shorter inter-injury intervals and reflect long-term astrogliosis induced by the cumulative injury.

RELEVANCE STATEMENT

Tensor scalar measurements, including L and q values, are potential DTI metrics for detecting long-term and subtle injury following rmTBI; in particular, q values may be used for quantifying remote white matter (WM) changes following rmTBI.

KEY POINTS

The alteration of L and q values was demonstrated after chronic repetitive mild traumatic brain injury. Changing q values were observed in the impact site and remote WM. The lower q values in the remote WM were associated with astrogliosis.

White matter and cortical gray matter microstructural abnormalities in new daily persistent headache: a NODDI study

BACKGROUND

New daily persistent headache (NDPH) is a rare primary headache with unclear pathogenesis. Neuroimaging studies of NDPH are limited, and controversy still exists. Diffusion tensor imaging (DTI) is commonly used to study the white matter. However, lacking specificity, the potential pathological mechanisms of white matter microstructural changes remain poorly understood. In addition, the intricacy of gray matter structures impedes the application of the DTI model. Here, we applied an advanced diffusion model of neurite orientation dispersion and density imaging (NODDI) to study the white matter and cortical gray matter microstructure in patients with NDPH.

METHODS

This study assessed brain microstructure, including 27 patients with NDPH, and matched 28 healthy controls (HCs) by NODDI. The differences between the two groups were assessed by tract-based spatial statistics (TBSS) and surface-based analysis (SBA), focusing on the NODDI metrics (neurite density index (NDI), orientation dispersion index (ODI), and isotropic volume fraction (ISOVF)). Furthermore, we performed Pearson's correlation analysis between the NODDI indicators and clinical characteristics.

RESULTS

Compared to HCs, patients with NDPH had a reduction of density and complexity in several fiber tracts. For robust results, the fiber tracts were defined as comprising more than 100 voxels, including bilateral inferior fronto-occipital fasciculus (IFOF), left superior longitudinal fasciculus (SLF) and inferior longitudinal fasciculus (ILF), as well as right corticospinal tract (CST). Moreover, the reduction of neurite density was uncovered in the left superior and middle frontal cortex, left precentral cortex, and right lateral orbitofrontal cortex and insula. There was no correlation between the NODDI metrics of these brain regions and clinical variables or scales of relevance after the Bonferroni correction.

CONCLUSIONS

Our research indicated that neurite loss was detected in both white matter and cortical gray matter of patients with NDPH.

Sex Differences in the Brain's White Matter Microstructure during Development assessed using Advanced Diffusion MRI Models

Typical sex differences in white matter (WM) microstructure during development are incompletely understood. Here we evaluated sex differences in WM microstructure during typical brain development using a sample of neurotypical individuals across a wide developmental age (N=239, aged 5-22 years). We used the conventional diffusion-weighted MRI (dMRI) model, diffusion tensor imaging (DTI), and two advanced dMRI models, the tensor distribution function (TDF) and neurite orientation dispersion density imaging (NODDI) to assess WM microstructure. WM microstructure exhibited significant, regionally consistent sex differences across the brain during typical development. Additionally, the TDF model was most sensitive in detecting sex differences. These findings highlight the importance of considering sex in neurodevelopmental research and underscore the value of the advanced TDF model.

Neurite orientation dispersion and density imaging reveals abnormal white matter and glymphatic function in active young boxers

The neurological effects and underlying pathophysiological mechanisms of sports-related concussion (SRC) in active young boxers remain poorly understood. This study aims to investigate the impairment of white matter microstructure and assess changes in glymphatic function following SRC by utilizing neurite orientation dispersion and density imaging (NODDI) on young boxers who have sustained SRC. A total of 60 young participants were recruited, including 30 boxers diagnosed with SRC and 30 healthy individuals engaging in regular exercise. The assessment of whole-brain white matter damage was conducted using diffusion metrics, while the evaluation of glymphatic function was performed through diffusion tensor imaging (DTI) analysis along the perivascular space (DTI-ALPS) index. A two-sample t-test was utilized to examine group differences in DTI and NODDI metrics. Spearman correlation and generalized linear mixed models were employed to investigate the relationship between clinical assessments of SRC and NODDI measurements. Significant alterations were observed in DTI and NODDI metrics among young boxers with SRC. Additionally, the DTI-ALPS index in the SRC group exhibited a significantly higher value than that of the control group (left side: 1.58 vs. 1.48, PFDR = 0.009; right side: 1.61 vs. 1.51, PFDR = 0.02). Moreover, it was observed that the DTI-ALPS index correlated with poorer cognitive test results among boxers in this study population. Repetitive SRC in active young boxers is associated with diffuse white matter injury and glymphatic dysfunction, highlighting the detrimental impact on brain health. These findings highlight the importance of long-term monitoring of the neurological health of boxers.

Cortical neurite microstructural correlates of time perception in healthy older adults

The human experience is significantly impacted by timing as it structures how information is processed. Nevertheless, the neurological foundation of time perception remains largely unresolved. Understanding cortical microstructure related to timing is crucial for gaining insight into healthy aging and recognizing structural alterations that are typical of neurodegenerative diseases associated with age. Given the importance, this study aimed to determine the brain regions that are accountable for predicting time perception in older adults using microstructural measures of the brain. In this study, elderly healthy adults performed the Time-Wall Estimation task to measure time perception through average error time. We used support vector regression (SVR) analyses to predict the average error time using cortical neurite microstructures derived from orientation dispersion and density imaging based on multi-shell diffusion magnetic resonance imaging (dMRI). We found significant correlations between observed and predicted average error times for neurite arborization (ODI) and free water (FISO). Neurite arborization and free water properties in specific regions in the medial and lateral prefrontal, superior parietal, and medial and lateral temporal lobes were among the most significant predictors of timing ability in older adults. Further, our results revealed that greater branching along with lower free water in cortical structures result in shorter average error times. Future studies should assess whether these same networks are contributing to time perception in older adults with mild cognitive impairment (MCI) and whether degeneration of these networks contribute to early diagnosis or detection of dementia.

Strain concentration drives the anatomical distribution of injury in acute and chronic traumatic brain injury

Brain tissue injury caused by mild traumatic brain injury (mTBI) disproportionately concentrates in the midbrain, cerebellum, mesial temporal lobe, and the interface between cortex and white matter at sulcal depths 1-12. The bio-mechanical principles that explain why physical impacts to different parts of the skull translate to common foci of injury concentrated in specific brain structures are unknown. A general and longstanding idea, which has not to date been directly tested in humans, is that different brain regions are differentially susceptible to strain loading11,13-15. We use Magnetic Resonance Elastography (MRE) in healthy participants to develop whole-brain bio-mechanical vulnerability maps that independently define which regions of the brain exhibit disproportionate strain concentration. We then validate those vulnerability maps in a prospective cohort of mTBI patients, using diffusion MRI data collected at three cross-sectional timepoints after injury: acute, sub-acute, chronic. We show that regions that exhibit high strain, measured with MRE, are also the sites of greatest injury, as measured with diffusion MR in mTBI patients. This was the case in acute, subacute, and chronic subgroups of the mTBI cohort. Follow-on analyses decomposed the biomechanical cause of increased strain by showing it is caused jointly by disproportionately higher levels of energy arriving to 'high-strain' structures, as well as the inability of 'high strain' structures to effectively disperse that energy. These findings establish a causal mechanism that explains the anatomy of injury in mTBI based on in vivo rheological properties of the human brain.

Sex differences in the extent of acute axonal pathologies after experimental concussion

Although human females appear be at a higher risk of concussion and suffer worse outcomes than males, underlying mechanisms remain unclear. With increasing recognition that damage to white matter axons is a key pathologic substrate of concussion, we used a clinically relevant swine model of concussion to explore potential sex differences in the extent of axonal pathologies. At 24 h post-injury, female swine displayed a greater number of swollen axonal profiles and more widespread loss of axonal sodium channels than males. Axon degeneration for both sexes appeared to be related to individual axon architecture, reflected by a selective loss of small caliber axons after concussion. However, female brains had a higher percentage of small caliber axons, leading to more extensive axon loss after injury compared to males. Accordingly, sexual dimorphism in axonal size is associated with more extensive axonal pathology in females after concussion, which may contribute to worse outcomes.

Diffusion tensor imaging in anisotropic tissues: application of reduced gradient vector schemes in peripheral nerves

BACKGROUND

In contrast to the brain, fibers within peripheral nerves have distinct monodirectional structure questioning the necessity of complex multidirectional gradient vector schemes for DTI. This proof-of-concept study investigated the diagnostic utility of reduced gradient vector schemes in peripheral nerve DTI.

METHODS

Three-Tesla magnetic resonance neurography of the tibial nerve using 20-vector DTI (DTI20) was performed in 10 healthy volunteers, 12 patients with type 2 diabetes, and 12 age-matched healthy controls. From the full DTI20 dataset, three reduced datasets including only two or three vectors along the x- and/or y- and z-axes were built to calculate major parameters. The influence of nerve angulation and intraneural connective tissue was assessed. The area under the receiver operating characteristics curve (ROC-AUC) was used for analysis.

RESULTS

Simplified datasets achieved excellent diagnostic accuracy equal to DTI20 (ROC-AUC 0.847-0.868, p ≤ 0.005), but compared to DTI20, the reduced models yielded mostly lower absolute values of DTI scalars: median fractional anisotropy (FA) ≤ 0.12; apparent diffusion coefficient (ADC) ≤ 0.25; axial diffusivity ≤ 0.96, radial diffusivity ≤ 0.07). The precision of FA and ADC with the three-vector model was closest to DTI20. Intraneural connective tissue was negatively correlated with FA and ADC (r ≥ -0.49, p < 0.001). Small deviations of nerve angulation had little effect on FA accuracy.

CONCLUSIONS

In peripheral nerves, bulk tissue DTI metrics can be approximated with only three predefined gradient vectors along the scanner's main axes, yielding similar diagnostic accuracy as a 20-vector DTI, resulting in substantial scan time reduction.

RELEVANCE STATEMENT

DTI bulk tissue parameters of peripheral nerves can be calculated with only three predefined gradient vectors at similar diagnostic performance as a standard DTI but providing a substantial scan time reduction.

KEY POINTS

• In peripheral nerves, DTI parameters can be approximated using only three gradient vectors. • The simplified model achieves a similar diagnostic performance as a standard DTI. • The simplified model allows for a significant acceleration of image acquisition. • This can help to introduce multi-b-value DTI techniques into clinical practice.

White Matter Alterations in Military Service Members With Remote Mild Traumatic Brain Injury

Importance

Mild traumatic brain injury (mTBI) is the signature injury experienced by military service members and is associated with poor neuropsychiatric outcomes. Yet, there is a lack of reliable clinical tools for mTBI diagnosis and prognosis.

Objective

To examine the white matter microstructure and neuropsychiatric outcomes of service members with a remote history of mTBI (ie, mTBI that occurred over 2 years ago) using diffusion tensor imaging (DTI) and neurite orientation dispersion and density imaging (NODDI).

Design, Setting, and Participants

This case-control study examined 98 male service members enrolled in a study at the National Intrepid Center of Excellence. Eligible participants were active duty status or able to enroll in the Defense Enrollment Eligibility Reporting system, ages 18 to 60 years, and had a remote history of mTBI; controls were matched by age.

Exposures

Remote history of mTBI.

Main Outcomes and Measures

White matter microstructure was assessed using a region-of-interest approach of skeletonized diffusion images, including DTI (fractional anisotropy, mean diffusivity, radial diffusivity and axial diffusivity) and NODDI (orientation dispersion index [ODI], isotropic volume fraction, intra-cellular volume fraction). Neuropsychiatric outcomes associated with posttraumatic stress disorder (PTSD) and postconcussion syndrome were assessed.

Results

A total of 65 male patients with a remote history of mTBI (mean [SD] age, 40.5 [5.0] years) and 33 age-matched male controls (mean [SD] age, 38.9 [5.6] years) were included in analysis. Compared with the control cohort, the 65 service members with mTBI presented with significantly more severe PTSD-like symptoms (mean [SD] PTSD CheckList-Civilian [PCL-C] version scores: control, 19.0 [3.8] vs mTBI, 41.2 [11.6]; P < .001). DTI and NODDI metrics were altered in the mTBI group compared with the control, including intra-cellular volume fraction of the right cortico-spinal tract (β = -0.029, Cohen d = 0.66; P < .001), ODI of the left posterior thalamic radiation (β = -0.006, Cohen d = 0.55; P < .001), and ODI of the left uncinate fasciculus (β = 0.013, Cohen d = 0.61; P < .001). In service members with mTBI, fractional anisotropy of the left uncinate fasciculus was associated with postconcussion syndrome (β = 5.4 × 10-3; P = .003), isotropic volume fraction of the genu of the corpus callosum with PCL-C (β = 4.3 × 10-4; P = .01), and ODI of the left fornix and stria terminalis with PCL-C avoidance scores (β = 1.2 × 10-3; P = .02).

Conclusions and Relevance

In this case-control study of military-related mTBI, the results suggest that advanced magnetic resonance imaging techniques using NODDI can reveal white matter microstructural alterations associated with neuropsychiatric symptoms in the chronic phase of mTBI. Diffusion trends observed throughout widespread white matter regions-of-interest may reflect mechanisms of neurodegeneration as well as postinjury tissue scarring and reorganization.

The Role of Puberty and Sex on Brain Structure in Adolescents With Anxiety Following Concussion

BACKGROUND

Adolescence represents a window of vulnerability for developing psychological symptoms following concussion, especially in girls. Concussion-related lesions in emotion regulation circuits may help explain these symptoms. However, the contribution of sex and pubertal maturation remains unclear. Using the neurite density index (NDI) in emotion regulation tracts (left/right cingulum bundle [CB], forceps minor [FMIN], and left/right uncinate fasciculus), we sought to elucidate these relationships.

METHODS

No adolescent had a history of anxiety and/or depression. The Screen for Child Anxiety Related Emotional Disorders and Children's Depression Rating Scale were used at scan to assess anxiety and depressive symptoms in 55 concussed adolescents (41.8% girls) and 50 control adolescents with no current/history of concussion (44% girls). We evaluated if a mediation-moderation model including the NDI (mediation) and sex or pubertal status (moderation) could help explain this relationship.

RESULTS

Relative to control adolescents, concussed adolescents showed higher anxiety (p = .003) and lower NDI, with those at more advanced pubertal maturation showing greater abnormalities in 4 clusters: the left CB frontal (p = .002), right CB frontal (p = .011), FMIN left-sided (p = .003), and FMIN right-sided (p = .003). Across all concussed adolescents, lower NDI in the left CB frontal and FMIN left-sided clusters partially mediated the association between concussion and anxiety, with the CB being specific to female adolescents. These effects did not explain depressive symptoms.

CONCLUSIONS

Our findings indicate that lower NDI in the CB and FMIN may help explain anxiety following concussion and that adolescents at more advanced (vs less advanced) status of pubertal maturation may be more vulnerable to concussion-related injuries, especially in girls.

Diffusion tensor imaging of the brain in children with sensory processing disorder: A review

Sensory processing disorder (SPD) is a clinical condition characterized by difficulties in the neurological processes of registering, discriminating, organizing, and responding to various sensory sensations. This study aimed to review the association between impaired white matter (WM) tract structure and neurofunctional deficits in children with SPD using diffusion tensor imaging (DTI). A comprehensive literature search was conducted using the online databases Google Scholar and PubMed (from 2010 to July 2023), resulting in the selection of nine relevant studies. Findings revealed that the splenium of the corpus callosum (SCC), superior longitudinal fasciculus (SLF), posterior corona radiata (PCR), and posterior thalamic radiation (PTR) exhibited reduced microstructural integrity, strongly associated with SPD. Specifically, auditory over-responsivity, a subtype of SPD, was linked to impaired integrity of the PCR, PTR, anterior corona radiata, and SLF. Tactile over-responsivity (TOR) was correlated with markers of decreased integrity in the SCC, superior corona radiata, and left PTR. Among the DTI parameters, decreased fractional anisotropy (FA) emerged as the most reliable factor for identifying SPD, followed by increased radial diffusivity (RD) and mean diffusivity (MD). Notably, significant correlations were observed between with auditory over-responsivity and TOR with the DTI parameters (positive for FA and negative for RD and MD). Overall, this review confirms the impaired integrity of specific WM tracts in children with SPD and establishes correlations between DTI parameters and neurobehavioral deficits associated with the disorder. The insights gained from this review contribute to a better understanding of SPD and hold clinical implications for its diagnosis and treatment.

Alteration of white matter microstructure in patients with sleep disorders after COVID-19 infection

BACKGROUND

The pathophysiology of coronasomnia remains unclear. This study aimed to investigate changes in white matter (WM) microstructure and inflammatory factors in patients with sleep disorders (SD) characterized by poor sleep quantity, quality, or timing following coronavirus disease 2019 (COVID-19) infection in the acute phase (within one month) and whether these changes could be recovered at 3-month follow-up.

METHODS

29 acute COVID-19 patients with SD (COVID_SD) and 27 acute COVID-19 patients without SD (COVID_NonSD) underwent diffusion tensor imaging (DTI), tested peripheral blood inflammatory cytokines level, and measured Pittsburgh Sleep Quality Index (PSQI), and matched 30 uninfected healthy controls. Analyzed WM abnormalities between groups in acute phase and explored its changes in COVID_SD at 3-month follow-up by using tract-based spatial statistics (TBSS). Correlations between DTI and clinical data were examined using Spearman partial correlation analysis.

RESULTS

Both COVID_SD and COVID_NonSD exhibited widespread WM microstructure abnormalities. The COVID_SD group showed specific WM microstructure changes in right inferior fronto-occipital fasciculus (IFOF) (lower fractional anisotropy [FA]/axial diffusivity [AD] and higher radial diffusivity [RD]) and left corticospinal tract (CST) (higher FA and lower RD) and higher interleukin-1β (IL-1β) compared with COVID_NonSD group. These WM abnormalities and IL-1β levels were correlated PSQI score. After 3 months, the IFOF integrity and IL-1β levels tended to return to normal accompanied by symptom improvement in the COVID_SD relative to baseline.

CONCLUSION

Abnormalities in right IFOF and left CST and elevated IL-1β levels were important neurophenotypes correlated with COVID_SD, which might provide new insights into the pathogenesis of neuroinflammation in SD patients induced by COVID-19.

Prediction of cognitive outcome after mild traumatic brain injury from acute measures of communication within brain networks

A considerable but ill-defined proportion of patients with mild traumatic brain injury (mTBI) experience persistent cognitive sequelae; the ability to identify such individuals early can help their neurorehabilitation. Here we tested the hypothesis that acute measures of efficient communication within brain networks are associated with patients' risk for unfavorable cognitive outcome six months after mTBI. Diffusion and T1-weighted magnetic resonance imaging, alongside cognitive measures, were obtained to map connectomes both one week and six months post injury in 113 adult patients with mTBI (71 males). For task-related brain networks, communication measures (characteristic path length, global efficiency, navigation efficiency) were moderately correlated with changes in cognition. Taking into account the covariance of age and sex, more unfavorable communication within networks were associated with worse outcomes within cognitive domains frequently impacted by mTBI (episodic and working memory, verbal fluency, inductive reasoning, and processing speed). Individuals with more unfavorable outcomes had significantly longer and less efficient pathways within networks supporting verbal fluency (all t > 2.786, p < .006), highlighting the vulnerability of language to mTBI. Participants in whom a task-related network was relatively inefficient one week post injury were up to eight times more likely to have unfavorable cognitive outcome pertaining to that task. Our findings suggest that communication measures within task-related networks identify mTBI patients who are unlikely to develop persistent cognitive deficits after mTBI. Our approach and findings can help to stratify mTBI patients according to their expected need for follow-up and/or neurorehabilitation.

White matter microstructure of children with sensory over-responsivity is associated with affective behavior

BACKGROUND

Sensory processing dysfunction (SPD) is linked to altered white matter (WM) microstructure in school-age children. Sensory over-responsivity (SOR), a form of SPD, affects at least 2.5% of all children and has substantial deleterious impact on learning and mental health. However, SOR has not been well studied using microstructural imaging such as diffusion MRI (dMRI). Since SOR involves hypersensitivity to external stimuli, we test the hypothesis that children with SOR require compensatory neuroplasticity in the form of superior WM microstructural integrity to protect against internalizing behavior, leaving those with impaired WM microstructure vulnerable to somatization and depression.

METHODS

Children ages 8-12 years old with neurodevelopmental concerns were assessed for SOR using a comprehensive structured clinical evaluation, the Sensory Processing 3 Dimensions Assessment, and underwent 3 Tesla MRI with multishell multiband dMRI. Tract-based spatial statistics was used to measure diffusion tensor imaging (DTI) and neurite orientation dispersion and density imaging (NODDI) metrics from global WM and nineteen selected WM tracts. Correlations of DTI and NODDI measures with measures of somatization and emotional disturbance from the Behavioral Assessment System for Children, 3rd edition (BASC-3), were computed in the SOR group and in matched children with neurodevelopmental concerns but not SOR.

RESULTS

Global WM fractional anisotropy (FA) is negatively correlated with somatization and with emotional disturbance in the SOR group but not the non-SOR group. Also observed in children with SOR are positive correlations of radial diffusivity (RD) and free water fraction (FISO) with somatization and, in most cases, emotional disturbance. These effects are significant in boys with SOR, whereas the study is underpowered for girls. The most affected white matter are medial lemniscus and internal capsule sensory tracts, although effects of SOR are observed in many cerebral, cerebellar, and brainstem tracts.

CONCLUSION

White matter microstructure is related to affective behavior in children with SOR.

Deep learning-based grading of white matter hyperintensities enables identification of potential markers in multi-sequence MRI data

BACKGROUND

White matter hyperintensities (WMHs) are widely-seen in the aging population, which are associated with cerebrovascular risk factors and age-related cognitive decline. At present, structural atrophy and functional alterations coexisted with WMHs lacks comprehensive investigation. This study developed a WMHs risk prediction model to evaluate WHMs according to Fazekas scales, and to locate potential regions with high risks across the entire brain.

METHODS

We developed a WMHs risk prediction model, which consisted of the following steps: T2 fluid attenuated inversion recovery (T2-FLAIR) image of each participant was firstly segmented into 1000 tiles with the size of 32 × 32 × 1, features from the tiles were extracted using the ResNet18-based feature extractor, and then a 1D convolutional neural network (CNN) was used to score all tiles based on the extracted features. Finally, a multi-layer perceptron (MLP) was constructed to predict the Fazekas scales based on the tile scores. The proposed model was trained using T2-FLAIR images, we selected tiles with abnormal scores in the test set after prediction, and evaluated their corresponding gray matter (GM) volume, white matter (WM) volume, fractional anisotropy (FA), mean diffusivity (MD), and cerebral blood flow (CBF) via longitudinal and multi-sequence Magnetic Resonance Imaging (MRI) data analysis.

RESULTS

The proposed WMHs risk prediction model could accurately predict the Fazekas ratings based on the tile scores from T2-FLAIR MRI images with accuracy of 0.656, 0.621 in training data set and test set, respectively. The longitudinal MRI validation revealed that most of the high-risk tiles predicted by the WMHs risk prediction model in the baseline images had WMHs in the corresponding positions in the longitudinal images. The validation on multi-sequence MRI demonstrated that WMHs were associated with GM and WM atrophies, WM micro-structural and perfusion alterations in high-risk tiles, and multi-modal MRI measures of most high-risk tiles showed significant associations with Mini Mental State Examination (MMSE) score.

CONCLUSION

Our proposed WMHs risk prediction model can not only accurately evaluate WMH severities according to Fazekas scales, but can also uncover potential markers of WMHs across modalities. The WMHs risk prediction model has the potential to be used for the early detection of WMH-related alterations in the entire brain and WMH-induced cognitive decline.

Relationship Between Microstructural Alterations and Cognitive Decline After Whole-Brain Radiation Therapy for Brain Metastases: An Exploratory Whole-Brain MR Analysis Based on Neurite Orientation Dispersion and Density Imaging

BACKGROUND

Cognitive impairment frequently occurs in patients with brain metastases (BM) after whole-brain radiotherapy (WBRT). It is crucial to explore the underlying mechanisms of cognitive impairment in BM patients receiving WBRT.

PURPOSE

To detect brain microstructural alterations in patients after WBRT by neurite orientation dispersion and density imaging (NODDI), and evaluate the performance of microstructural alterations in predicting cognitive impairment.

STUDY TYPE

Prospective.

POPULATION

Twenty-six patients (seven female; mean age, 60.9 years).

FIELD STRENGTH/SEQUENCE

3-T, multi-shell diffusion-weighted single-shot echo-planar sequence. Three-dimensional magnetization-prepared rapid acquisition with gradient echo sequence.

ASSESSMENT

Mini-mental state examination (MMSE) evaluations were conducted prior to, following, 1 and 3 months after WBRT. The diffusion data were collected twice, 1 week before and 1 week after WBRT. NODDI analysis was conducted to assess microstructural alterations in whole brain (orientation dispersion index, neurite density index, volume fraction of isotropic water molecules). Reliable change indices (RCI) of MMSE were used to measure cognitive decline. The performance of support vector machine models based on NODDI parameters and clinical features (prednisone usage, tumor volume, etc.) in predicting MMSE-RCI was evaluated.

STATISTICAL TESTS

Paired t-test to assess alterations of NODDI measures and MMSE during follow-up. Statistical significance level of P-value <0.05.

RESULTS

Significantly decreased MMSE score was found at 3 months after WBRT. After WBRT, corpus callosum, medial prefrontal cortex, limbic lobe, occipital lobe, parietal lobe, putamen, globus pallidus lentiform, and thalamus demonstrated damage in NODDI parameters. The predicted MMSE-RCI based on NODDI features was significantly associated with the measured MMSE-RCI at 1 month (R = 0.573; P = 0.003) and 3 months (R = 0.687; P < 0.0001) after WBRT.

DATA CONCLUSION

Microstructural alterations in several brain regions including the middle prefrontal and limbic cortexes were observed in patients with BM following WBRT, which may contribute to subsequent cognitive decline.

EVIDENCE LEVEL

2 TECHNICAL EFFICACY: Stage 2.

Evidence of Ongoing Cerebral Microstructural Reorganization in Children With Persisting Symptoms Following Mild Traumatic Brain Injury: A NODDI DTI Analysis

Approximately 300-550 children per 100,000 sustain a mild traumatic brain injury (mTBI) each year, of whom ∼25-30% have long-term cognitive problems. Following mTBI, free water (FW) accumulation occurs in white matter (WM) tracts. Diffusion tensor imaging (DTI) can be used to investigate structural integrity following mTBI. Compared with conventional DTI, neurite orientation dispersion and density imaging (NODDI) orientation dispersion index (ODI) and fraction of isolated free water (FISO) metrics may allow a more advanced insight into microstructural damage following pediatric mTBI. In this longitudinal study, we used NODDI to explore whole-brain and tract-specific differences in ODI and FISO in children with persistent symptoms after mTBI (n = 80) and in children displaying clinical recovery (n = 32) at 1 and 2-3 months post-mTBI compared with healthy controls (HCs) (n = 21). Two-way repeated measures analysis of variance (ANOVA) and voxelwise two-sample t tests were conducted to compare whole-brain and tract-specific diffusion across groups. All results were corrected at positive false discovery rate (pFDR) <0.05. We also examined the association between NODDI metrics and clinical outcomes, using logistical regression to investigate the value of NODDI metrics in predicting future recovery from mTBI. Whole-brain ODI was significantly increased in symptomatic participants compared with HCs at both 1 and 2 months post-injury, where the uncinate fasciculus (UF) and inferior fronto-occipital fasciculus (IFOF) were particularly implicated. Using region of interest (ROI) analysis in significant WM, bilateral IFOF and UF voxels, symptomatic participants had the highest ODI in all ROIs. ODI was lower in asymptomatic participants, and HCs had the lowest ODI in all ROIs. No changes in FISO were found across groups or over time. WM ODI was moderately correlated with a higher youth-reported post-concussion symptom inventory (PCSI) score. With 87% predictive power, ODI (1 month post-injury) and clinical predictors (age, sex, PCSI score, attention scores) were a more sensitive predictor of recovery at 2-3 months post-injury than fractional anisotropy (FA) and clinical predictors, or clinical predictors alone. FISO could not predict recovery at 2-3 months post-injury. Therefore, we found that ODI was significantly increased in symptomatic children following mTBI compared with HCs at 1 month post-injury, and progressively decreased over time alongside clinical recovery. We found no significant differences in FISO between groups or over time. WM ODI at 1 month was a more sensitive predictor of clinical recovery at 2-3 months post-injury than FA, FISO, or clinical measures alone. Our results show evidence of ongoing microstructural reorganization or neuroinflammation between 1 and 2-3 months post-injury, further supporting delayed return to play in children who remain symptomatic. We recommend future research examining the clinical utility of NODDI following mTBI to predict recovery or persistence of post-concussion symptoms and thereby inform management of mTBI.

Traveling Subject-Informed Harmonization Increases Reliability of Brain Diffusion Tensor and Neurite Mapping

Diffusion-weighted magnetic resonance imaging (dMRI) of brain has helped elucidate the microstructural changes of psychiatric and neurodegenerative disorders. Inconsistency between MRI models has hampered clinical application of dMRI-based metrics. Using harmonized dMRI data of 300 scans from 69 traveling subjects (TS) scanning the same individuals at multiple conditions with 13 MRI models and 2 protocols, the widely-used metrics such as diffusion tensor imaging (DTI) and neurite orientation dispersion and density imaging (NODDI) were evaluated before and after harmonization with a combined association test (ComBat) or TS-based general linear model (TS-GLM). Results showed that both ComBat and TS-GLM significantly reduced the effects of the MRI site, model, and protocol for diffusion metrics while maintaining the intersubject biological effects. The harmonization power of TS-GLM based on TS data model is more powerful than that of ComBat. In conclusion, our research demonstrated that although ComBat and TS-GLM harmonization approaches were effective at reducing the scanner effects of the site, model, and protocol for DTI and NODDI metrics in WM, they exhibited high retainability of biological effects. Therefore, we suggest that, after harmonizing DTI and NODDI metrics, a multisite study with large cohorts can accurately detect small pathological changes by retaining pathological effects.

White matter microstructural disruption in minimal hepatic encephalopathy: a neurite orientation dispersion and density imaging (NODDI) study

PURPOSE

To evaluate the ability of neurite orientation dispersion and density imaging (NODDI) for detecting white matter (WM) microstructural abnormalities in minimal hepatic encephalopathy (MHE).

METHODS

Diffusion-weighted images, enabling the estimation of NODDI and diffusion tensor imaging (DTI) parameters, were acquired from 20 healthy controls (HC), 22 cirrhotic patients without MHE (NHE), and 15 cirrhotic patients with MHE. Tract-based spatial statistics were used to determine differences in DTI (including fractional anisotropy [FA] and mean/axial/radial diffusivity [MD/AD/RD]) and NODDI parameters (including neurite density index [NDI], orientation dispersion index [ODI], and isotropic volume fraction [ISO]). Voxel-wise analyses of correlations between diffusion parameters and neurocognitive performance determined by Psychometric Hepatic Encephalopathy Score (PHES) were completed.

RESULTS

MHE patients had extensive NDI reduction and rare ODI reduction, primarily involving the genu and body of corpus callosum and the bilateral frontal lobe, corona radiata, external capsule, anterior limb of internal capsule, temporal lobe, posterior thalamic radiation, and brainstem. The extent of NDI and ODI reduction expanded from NHE to MHE. In both MHE and NHE groups, the extent of NDI change was quite larger than that of FA change. No significant intergroup difference in ISO/MD/AD/RD was observed. Tissue specificity afforded by NODDI revealed the underpinning of FA reduction in MHE. The NDI in left frontal lobe was significantly correlated with PHES.

CONCLUSION

MHE is characterized by diffuse WM microstructural impairment (especially neurite density reduction). NODDI can improve the detection of WM microstructural impairments in MHE and provides more precise information about MHE-related pathology than DTI.

The relationship between cognition and white matter tract damage after mild traumatic brain injury in a premorbidly healthy, hospitalised adult cohort during the post-acute period

Introduction

Recent developments in neuroimaging techniques enable increasingly sensitive consideration of the cognitive impact of damage to white matter tract (WMT) microstructural organisation after mild traumatic brain injury (mTBI).

Objective

This study investigated the relationship between WMT microstructural properties and cognitive performance.

Participants setting and design

Using an observational design, a group of 26 premorbidly healthy adults with mTBI and a group of 20 premorbidly healthy trauma control (TC) participants who were well-matched on age, sex, premorbid functioning and a range of physical, psychological and trauma-related variables, were recruited following hospital admission for traumatic injury.

Main measures

All participants underwent comprehensive unblinded neuropsychological examination and structural neuroimaging as outpatients 6-10 weeks after injury. Neuropsychological examination included measures of speed of processing, attention, memory, executive function, affective state, pain, fatigue and self-reported outcome. The WMT microstructural properties were estimated using both diffusion tensor imaging (DTI) and neurite orientation dispersion and density imaging (NODDI) modelling techniques. Tract properties were compared between the corpus callosum, inferior longitudinal fasciculus, uncinate fasciculus, anterior corona radiata and three segmented sections of the superior longitudinal fasciculus.

Results

For the TC group, in all investigated tracts, with the exception of the uncinate fasciculus, two DTI metrics (fractional anisotropy and apparent diffusion coefficient) and one NODDI metric (intra-cellular volume fraction) revealed expected predictive linear relationships between extent of WMT microstructural organisation and processing speed, memory and executive function. The mTBI group showed a strikingly different pattern relative to the TC group, with no relationships evident between WMT microstructural organisation and cognition on most tracts.

Conclusion

These findings indicate that the predictive relationship that normally exists in adults between WMT microstructural organisation and cognition, is significantly disrupted 6-10 weeks after mTBI and suggests that WMT microstructural organisation and cognitive function have disparate recovery trajectories.

Repeatability of neurite orientation dispersion and density imaging in patients with traumatic brain injury

BACKGROUND AND PURPOSE

The aim of this study was to assess the repeatability of neurite orientation dispersion and density imaging in healthy controls (HCs) and traumatic brain injury (TBI).

METHODS

Seventeen HCs and 48 TBI patients were scanned twice over 18 weeks with diffusion imaging. Orientation dispersion (ODI), neurite density (NDI), and the fraction of isotropic diffusion (F-ISO) were quantified in regions of interest (ROIs) from a gray matter, subcortical, and white matter atlas and compared using the coefficient of variation for repeated measures (CVrep ), which quantifies the expected percent change on repeated measurement. We used a modified signed likelihood ratio test (M-SLRT) to compare the CVrep between groups in each ROI while correcting for multiple comparisons.

RESULTS

NDI exhibited excellent repeatability in both groups; the only group difference was found in the fusiform gyrus, where HCs exhibited better repeatability (M-SLRT = 9.463, p = .0021). ODI also had excellent repeatability in both groups, although repeatability was significantly better in HCs in 16 cortical ROIs (p < .0022) and in the bilateral white matter and bilateral cortex (p < .0027). F-ISO exhibited relatively poor repeatability in both groups, with few group differences.

CONCLUSION

Overall, the repeatability of the NDI, ODI, and F-ISO metrics over an 18-week period is acceptable for assessing the effects of behavioral or pharmacological interventions, though caution is advised when assessing F-ISO changes over time.

Military-related mild traumatic brain injury: clinical characteristics, advanced neuroimaging, and molecular mechanisms

Mild traumatic brain injury (mTBI) is a significant health burden among military service members. Although mTBI was once considered relatively benign compared to more severe TBIs, a growing body of evidence has demonstrated the devastating neurological consequences of mTBI, including chronic post-concussion symptoms and deficits in cognition, memory, sleep, vision, and hearing. The discovery of reliable biomarkers for mTBI has been challenging due to under-reporting and heterogeneity of military-related mTBI, unpredictability of pathological changes, and delay of post-injury clinical evaluations. Moreover, compared to more severe TBI, mTBI is especially difficult to diagnose due to the lack of overt clinical neuroimaging findings. Yet, advanced neuroimaging techniques using magnetic resonance imaging (MRI) hold promise in detecting microstructural aberrations following mTBI. Using different pulse sequences, MRI enables the evaluation of different tissue characteristics without risks associated with ionizing radiation inherent to other imaging modalities, such as X-ray-based studies or computerized tomography (CT). Accordingly, considering the high morbidity of mTBI in military populations, debilitating post-injury symptoms, and lack of robust neuroimaging biomarkers, this review (1) summarizes the nature and mechanisms of mTBI in military settings, (2) describes clinical characteristics of military-related mTBI and associated comorbidities, such as post-traumatic stress disorder (PTSD), (3) highlights advanced neuroimaging techniques used to study mTBI and the molecular mechanisms that can be inferred, and (4) discusses emerging frontiers in advanced neuroimaging for mTBI. We encourage multi-modal approaches combining neuropsychiatric, blood-based, and genetic data as well as the discovery and employment of new imaging techniques with big data analytics that enable accurate detection of post-injury pathologic aberrations related to tissue microstructure, glymphatic function, and neurodegeneration. Ultimately, this review provides a foundational overview of military-related mTBI and advanced neuroimaging techniques that merit further study for mTBI diagnosis, prognosis, and treatment monitoring.

Machine learning-based classification of chronic traumatic brain injury using hybrid diffusion imaging

Background and purpose

Traumatic brain injury (TBI) can cause progressive neuropathology that leads to chronic impairments, creating a need for biomarkers to detect and monitor this condition to improve outcomes. This study aimed to analyze the ability of data-driven analysis of diffusion tensor imaging (DTI) and neurite orientation dispersion imaging (NODDI) to develop biomarkers to infer symptom severity and determine whether they outperform conventional T1-weighted imaging.

Materials and methods

A machine learning-based model was developed using a dataset of hybrid diffusion imaging of patients with chronic traumatic brain injury. We first extracted the useful features from the hybrid diffusion imaging (HYDI) data and then used supervised learning algorithms to classify the outcome of TBI. We developed three models based on DTI, NODDI, and T1-weighted imaging, and we compared the accuracy results across different models.

Results

Compared with the conventional T1-weighted imaging-based classification with an accuracy of 51.7-56.8%, our machine learning-based models achieved significantly better results with DTI-based models at 58.7-73.0% accuracy and NODDI with an accuracy of 64.0-72.3%.

Conclusion

The machine learning-based feature selection and classification algorithm based on hybrid diffusion features significantly outperform conventional T1-weighted imaging. The results suggest that advanced algorithms can be developed for inferring symptoms of chronic brain injury using feature selection and diffusion-weighted imaging.

Diffusion tensor imaging in the courtroom: Distinction between scientific specificity and legally admissible evidence

Interest and uptake of science and medicine peer-reviewed literature by readers outside of a paper’s topical subject, field or even discipline is ever-expanding. While the application of knowledge from one field or discipline to others can stimulate innovative solutions to problems facing modern society, it is also fraught with danger for misuse. In the practice of law in the United States, academic papers are submitted to the courts as evidence in personal injury litigation from both the plaintiff (complainant) and defendant. Such transcendence of an academic publication over disciplinary boundaries is immediately met with the challenge of application by a group that inherently lacks in-depth knowledge on the scientific method, the practice of evidence-based medicine, or the publication process as a structured and internationally synthesized process involving peer review and guided by ethical standards and norms. A modern-day example of this is the ongoing conflict between the sensitivity of diffusion tensor imaging (DTI) and the legal standards for admissibility of evidence in litigation cases of mild traumatic brain injury (mTBI). In this review, we amalgamate the peer-reviewed research on DTI in mTBI with the court’s rationale underlying decisions to admit or exclude evidence of DTI abnormalities to support claims of brain injury. We found that the papers which are critical of the use of DTI in the courtroom reflect a primary misunderstanding about how diagnostic biomarkers differ legally from relevant and admissible evidence. The clinical use of DTI to identify white matter abnormalities in the brain at the chronic stage is a valid methodology both clinically as well as forensically, contributes data that may or may not corroborate the existence of white matter damage, and should be admitted into evidence in personal injury trials if supported by a clinician. We also delve into an aspect of science publication and peer review that can be manipulated by scientists and clinicians to publish an opinion piece and misrepresent it as an unbiased, evidence-based, systematic research article in court cases, the decisions of which establish precedence for future cases and have implications on future legislation that will impact the lives of every citizen and erode the integrity of science and medicine practitioners.

Dynamic structural remodeling of the human visual system prompted by bilateral retinal gene therapy

The impact of changes in visual input on neuronal circuitry is complex and much of our knowledge on human brain plasticity of the visual systems comes from animal studies. Reinstating vision in a group of patients with low vision through retinal gene therapy creates a unique opportunity to dynamically study the underlying process responsible for brain plasticity. Historically, increases in the axonal myelination of the visual pathway has been the biomarker for brain plasticity. Here, we demonstrate that to reach the long-term effects of myelination increase, the human brain may undergo demyelination as part of a plasticity process. The maximum change in dendritic arborization of the primary visual cortex and the neurite density along the geniculostriate tracks occurred at three months (3MO) post intervention, in line with timing for the peak changes in postnatal synaptogenesis within the visual cortex reported in animal studies. The maximum change at 3MO for both the gray and white matter significantly correlated with patients' clinical responses to light stimulations called full field sensitivity threshold (FST). Our results shed a new light on the underlying process of brain plasticity by challenging the concept of increase myelination being the hallmark of brain plasticity and instead reinforcing the idea of signal speed optimization as a dynamic process for brain plasticity.

Structural brain connectivity predicts early acute pain after mild traumatic brain injury

ABSTRACT

Mild traumatic brain injury (mTBI), is a leading cause of disability worldwide, with acute pain manifesting as one of its most debilitating symptoms. Understanding acute postinjury pain is important because it is a strong predictor of long-term outcomes. In this study, we imaged the brains of 157 patients with mTBI, following a motorized vehicle collision. We extracted white matter structural connectivity networks and used a machine learning approach to predict acute pain. Stronger white matter tracts within the sensorimotor, thalamiccortical, and default-mode systems predicted 20% of the variance in pain severity within 72 hours of the injury. This result generalized in 2 independent groups: 39 mTBI patients and 13 mTBI patients without whiplash symptoms. White matter measures collected at 6 months after the collision still predicted mTBI pain at that timepoint (n = 36). These white matter connections were associated with 2 nociceptive psychophysical outcomes tested at a remote body site-namely, conditioned pain modulation and magnitude of suprathreshold pain-and with pain sensitivity questionnaire scores. Our findings demonstrate a stable white matter network, the properties of which determine an important amount of pain experienced after acute injury, pinpointing a circuitry engaged in the transformation and amplification of nociceptive inputs to pain perception.

The Current State of Functional MR Imaging for Trauma Prognostication

In this review, we discuss the basics of functional MRI (fMRI) techniques including task-based and resting state fMRI, and overview the major findings in patients with traumatic brain injury. We summarize the studies that have longitudinally evaluated the changes in brain connectivity and task-related activation in trauma patients during different phases of trauma. We discuss how these data may potentially be used for prognostication, treatment planning, or monitoring and management of trauma patients.

Associations between psychological resilience and metrics of white matter microstructure in pediatric concussion

This study investigated associations between psychological resilience and characteristics of white matter microstructure in pediatric concussion. This is a case control study and a planned substudy of a larger randomized controlled trial. Children with an acute concussion or orthopedic injury were recruited from the emergency department. Participants completed both the Connor-Davidson Resilience Scale 10 and an MRI at 72 h and 4-weeks post-injury. The association between resiliency and fractional anisotropy (FA), mean diffusivity (MD), axial diffusivity (AD), and radial diffusivity (RD) at both timepoints were examined. We examined whether these associations were moderated by group. The association between resiliency captured at 72 h and diffusion tensor imaging metrics at 4 weeks was also investigated. Clusters were extracted using a significance threshold of threshold-free cluster enhancement corrected p < .05. A total of 66 children with concussion (median (IQR) age = 12.88 (IQR: 11.80-14.36); 47% female) and 29 children with orthopedic-injury (median (IQR) age = 12.49 (IQR: 11.18-14.01); 41% female) were included. A negative correlation was identified in the concussion group between 72 h resilience and 72 h FA. Meanwhile, positive correlations were identified in the concussion group with concussion between 72 h resilience and both 72 h MD and 72 h RD. These findings suggest that 72 h resilience is associated with white matter microstructure of the forceps minor, superior longitudinal fasciculus, and anterior thalamic radiation at 72 h post-concussion. Resilience seems to be associated with neural integrity only in the acute phase of concussion and thus may be considered when researching concussion recovery.

Current State of Diffusion-Weighted Imaging and Diffusion Tensor Imaging for Traumatic Brain Injury Prognostication

Advanced imaging techniques are needed to assist in providing a prognosis for patients with traumatic brain injury (TBI), particularly mild TBI (mTBI). Diffusion tensor imaging (DTI) is one promising advanced imaging technique, but has shown variable results in patients with TBI and is not without limitations, especially when considering individual patients. Efforts to resolve these limitations are being explored and include developing advanced diffusion techniques, creating a normative database, improving study design, and testing machine learning algorithms. This article will review the fundamentals of DTI, providing an overview of the current state of its utility in evaluating and providing prognosis in patients with TBI.

Hemispheric lateralization of white matter microstructure in children and its potential role in sensory processing dysfunction

Diffusion tensor imaging (DTI) studies have demonstrated white matter microstructural differences between the left and right hemispheres of the brain. However, the basis of these hemispheric asymmetries is not yet understood in terms of the biophysical properties of white matter microstructure, especially in children. There are reports of altered hemispheric white matter lateralization in ASD; however, this has not been studied in other related neurodevelopmental disorders such as sensory processing disorder (SPD). Firstly, we postulate that biophysical compartment modeling of diffusion MRI (dMRI), such as Neurite Orientation Dispersion and Density Imaging (NODDI), can elucidate the hemispheric microstructural asymmetries observed from DTI in children with neurodevelopmental concerns. Secondly, we hypothesize that sensory over-responsivity (SOR), a common type of SPD, will show altered hemispheric lateralization relative to children without SOR. Eighty-seven children (29 females, 58 males), ages 8-12 years, presenting at a community-based neurodevelopmental clinic were enrolled, 48 with SOR and 39 without. Participants were evaluated using the Sensory Processing 3 Dimensions (SP3D). Whole brain 3 T multi-shell multiband dMRI (b = 0, 1,000, 2,500 s/mm2) was performed. Tract Based Spatial Statistics were used to extract DTI and NODDI metrics from 20 bilateral tracts of the Johns Hopkins University White-Matter Tractography Atlas and the lateralization Index (LI) was calculated for each left-right tract pair. With DTI metrics, 12 of 20 tracts were left lateralized for fractional anisotropy and 17/20 tracts were right lateralized for axial diffusivity. These hemispheric asymmetries could be explained by NODDI metrics, including neurite density index (18/20 tracts left lateralized), orientation dispersion index (15/20 tracts left lateralized) and free water fraction (16/20 tracts lateralized). Children with SOR served as a test case of the utility of studying LI in neurodevelopmental disorders. Our data demonstrated increased lateralization in several tracts for both DTI and NODDI metrics in children with SOR, which were distinct for males versus females, when compared to children without SOR. Biophysical properties from NODDI can explain the hemispheric lateralization of white matter microstructure in children. As a patient-specific ratio, the lateralization index can eliminate scanner-related and inter-individual sources of variability and thus potentially serve as a clinically useful imaging biomarker for neurodevelopmental disorders.